Tutorials

Tutorials

Introductory - Essential reading. This will give you a basic introduction to the way MVPA works, and what you can do with it. Many of the other tutorials build on the SUBJ structure that this tutorial builds.

• SPM based Intro - The same tutorial as above except handling spm files instead of afni briks.

Advanced - A series of short guides showing in-depth how to do several common tasks. Definitely worth reading.

Averaging - A brief tutorial on how to average timepoints together.

Using AFNI's GLM (3dDeconvolve) for voxel selection. This talks you through n-1 feature selection using AFNI's general linear model, all being controlled by the MVPA toolbox from within Matlab.

Classification-related tips and tricks.

• Creating 'importance maps' based on classifier weights

• Spherical searchlights for voxel selection and brain maps.

• Using AdaBoost for classification

EBC tutorial - For those who participated in the EBC competition or want another dataset to work with. This will guide you through using the EBC Expansion to the MVPA Toolbox.

Visualizing your data in various ways.

Writing unit tests for MVPA functions